In vivo validation of a one-dimensional finite-element method for predicting blood flow in cardiovascular bypass grafts

Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments and does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described a new approach to vascular surgery planning based on solving the governing equations...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2003-06, Vol.50 (6), p.649-656
Main Authors: Steele, B.N., Jing Wan, Ku, J.P., Hughes, T.J.R., Taylor, C.A.
Format: Article
Language:English
Subjects:
Anastomosis, Surgical
Animals
Aorta, Thoracic - physiopathology
Aorta, Thoracic - surgery
Biological and medical sciences
Biomedical materials
Blood flow
Blood Flow Velocity
Bypasses
Cardiology
Computational modeling
Computer Simulation
Constriction, Pathologic - physiopathology
Coronary Artery Bypass
Distributed computing
Equations
Finite Element Analysis
Finite element methods
Flow rate
Fluid flow measurement
Graft Occlusion, Vascular - physiopathology
In vivo
In vivo tests
Magnetic resonance imaging
Magnetic Resonance Imaging - methods
Mathematical analysis
Mathematical models
Medical sciences
Models, Cardiovascular
Preoperative Care - methods
Surgery
Surgery, Computer-Assisted - methods
Surgical implants
Swine
Thoracic Arteries - physiopathology
Thoracic Arteries - surgery
Transplants
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Description
Summary:Current practice in vascular surgery utilizes only diagnostic and empirical data to plan treatments and does not enable quantitative a priori prediction of the outcomes of interventions. We have previously described a new approach to vascular surgery planning based on solving the governing equations of blood flow in patient-specific models. A one-dimensional finite-element method was used to simulate blood flow in eight porcine thoraco-thoraco aortic bypass models. The predicted flow rate was compared to in vivo data obtained using cine phase-contrast magnetic resonance imaging. The mean absolute difference between computed and measured flow distribution in the stenosed aorta was found to be 4.2% with the maximum difference of 10.6% and a minimum difference of 0.4%. Furthermore, the sensitivity of the flow rate and distribution with respect to stenosis and branch losses were quantified.
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2003.812201